The ordinary least squares (OLS) estimator for spatial autoregressions may be consistent as pointed out by Lee (2002), provided that each spatial unit is influenced aggregately by a significant portion of the total units. This paper presents a unified asymptotic distribution result of the...

We investigate the finite-sample bias of the quasi-maximum likelihood estimator (QMLE) in spatial autoregressive models with possible exogenous regressors. We derive the approximate bias result of the QMLE in terms of model parameters and also the moments (up to order 4) of the error...

In this study, I investigate the necessary condition for consistency of the maximum likelihood estimator (MLE) of spatial models with a spatial moving average process in the disturbance term. I show that the MLE of spatial autoregressive and spatial moving average parameters is generally...

In this study, I investigate the necessary condition for the consistency of the maximum likelihood estimator (MLE) of spatial models with a spatial moving average process in the disturbance term. I show that the MLE of spatial autoregressive and spatial moving average parameters is generally...

In this paper, we introduce the one-step generalized method of moments (GMM) estimation methods considered in Lee (2007a) and Liu, Lee, and Bollinger (2010) to a spatial autoregressive model that has a spatial moving average process in the disturbance term (for short SARMA (1,1)). First, we...

In this paper, we introduce the one-step generalized method of moments (GMM) estimation methods considered in Lee (2007a) and Liu, Lee, and Bollinger (2010) to spatial models that impose a spatial moving average process for the disturbance term. First, we determine the set of best linear and...

A new class of regression type models termed essentially linear models is proposed. The class is characterized by geometric considerations. Within the class the distribution of the maximum likelihood estimator is easily approximated by a natural extension of the p*-formula even though the MLE...

A new class of regression type models termed essentially linear models is proposed. The class is characterized by geometric considerations. Within the class the distribution of the maximum likelihood estimator is easily approximated by a natural extension of the pstar-formula even though the MLE...

We provide general results for the asymptotic variance of regression coefficients computedfrom a sample drawn from a finite population. We encompass the potentialoutcomes and classic regression frameworks allowing for both heterogeneous treatmenteffects and random-across-resampling shocks....

We provide general results for the asymptotic variance of regression coefficients computed from a sample drawn from a finite population. We encompass the potential outcomes and classic regression frameworks allowing for both heterogeneous treatment effects and random-across-resampling shocks....